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- Baltar, Valéria Troncoso, et al.
(författare)
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A structural equation modelling approach to explore the role of B vitamins and immune markers in lung cancer risk
- 2013
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Ingår i: European Journal of Epidemiology. - : Springer Science and Business Media LLC. - 0393-2990 .- 1573-7284. ; 28:8, s. 677-688
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Tidskriftsartikel (refereegranskat)abstract
- The one-carbon metabolism (OCM) is considered key in maintaining DNA integrity and regulating gene expression, and may be involved in the process of carcinogenesis. Several B-vitamins and amino acids have been implicated in lung cancer risk, via the OCM directly as well as immune system activation. However it is unclear whether these factors act independently or through complex mechanisms. The current study applies structural equations modelling (SEM) to further disentangle the mechanisms involved in lung carcinogenesis. SEM allows simultaneous estimation of linear relations where a variable can be the outcome in one equation and the predictor in another, as well as allowing estimation using latent variables (factors estimated by correlation matrix). A large number of biomarkers have been analysed from 891 lung cancer cases and 1,747 controls nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Four putative mechanisms in the OCM and immunity were investigated in relation to lung cancer risk: methionine-homocysteine metabolism, folate cycle, transsulfuration, and mechanisms involved in inflammation and immune activation, all adjusted for tobacco exposure. The hypothesized SEM model confirmed a direct and protective effect for factors representing methionine-homocysteine metabolism (p = 0.020) and immune activation (p = 0.021), and an indirect protective effect of folate cycle (p = 0.019), after adjustment for tobacco smoking. In conclusion, our results show that in the investigation of the involvement of the OCM, the folate cycle and immune system in lung carcinogenesis, it is important to consider complex pathways (by applying SEM) rather than the effects of single vitamins or nutrients (e.g. using traditional multiple regression). In our study SEM were able to suggest a greater role of the methionine-homocysteine metabolism and immune activation over other potential mechanisms.
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| 2. |
- Brand, Judith S., et al.
(författare)
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Age at Menopause, Reproductive Life Span, and Type 2 Diabetes Risk
- 2013
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Ingår i: Diabetes Care. - : American Diabetes Association. - 0149-5992 .- 1935-5548. ; 36:4, s. 1012-1019
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE-Age at menopause is an important determinant of future health outcomes, but little is known about its relationship with type 2 diabetes. We examined the associations of menopausal age and reproductive life span (menopausal age minus menarcheal age) with diabetes risk.RESEARCH DESIGN AND METHODS-Data were obtained from the InterAct study, a prospective case-cohort study nested within the European Prospective Investigation into Cancer and Nutrition. A total of 3,691 postmenopausal type 2 diabetic case subjects and 4,408 subcohort members were included in the analysis, with a median follow-up of 11 years. Prentice weighted Cox proportional hazards models were adjusted for age, known risk factors for diabetes, and reproductive factors, and effect modification by BMI, waist circumference, and smoking was studied.RESULTS-Mean (SD) age of the subcohort was 59.2 (5.8) years. After multivariable adjustment, hazard ratios (HRs) of type 2 diabetes were 1.32 (95% CI 1.04-1.69), 1.09 (0.90-1.31), 0.97 (0.86-1.10), and 0.85 (0.70-1.03) for women with menopause at ages <40, 40-44, 45-49, and >= 55 years, respectively, relative to those with menopause at age 50-54 years. The HR per SD younger age at menopause was 1.08 (1.02-1.14). Similarly, a shorter reproductive life span was associated with a higher diabetes risk (HR per SD lower reproductive life span 1.06 [ 1.01-1.12]). No effect modification by BMI, waist circumference, or smoking was observed (P interaction all > 0.05).CONCLUSIONS-Early menopause is associated with a greater risk of type 2 diabetes. Diabetes Care 36:1012-1019, 2013
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